###################################### The Python Performance Benchmark Suite ###################################### The ``pyperformance`` project is intended to be an authoritative source of benchmarks for all Python implementations. The focus is on real-world benchmarks, rather than synthetic benchmarks, using whole applications when possible. * `pyperformance documentation `_ * `pyperformance GitHub project `_ (source code, issues) * `Download pyperformance on PyPI `_ pyperformance is distributed under the MIT license. Documentation: .. toctree:: :maxdepth: 2 usage benchmarks custom_benchmarks cpython_results_2017 changelog Other Python Benchmarks: * CPython: `speed.python.org `_ uses pyperf, pyperformance and `Codespeed `_ (Django web application) * PyPy: `speed.pypy.org `_ uses `PyPy benchmarks `_ * Pyston: `pyston-perf `_ and `speed.pyston.org `_ * `Numba benchmarks `_ * Cython: `Cython Demos/benchmarks `_ * pythran: `numpy-benchmarks `_ See also the `Python speed mailing list `_ and the `Python pyperf module `_ (used by pyperformance). pyperformance is not tuned for PyPy yet: use the `PyPy benchmarks project `_ instead to measure PyPy performances. Image generated by bm_raytrace (pure Python raytrace): .. image:: images/bm_raytrace.jpg :alt: Pure Python raytracer